A proportional integral derivative (PID) controller implements control over a drilling system based on an integral term and a proportional term. The integral term is the integral of an operating drilling fluid pressure compared to a target drilling fluid pressure. The proportional term is the difference between an operating weight on bit and a target weight on bit. The sum of the proportional term and the integral term is multiplied by a controller parameter to determine a surface rate of penetration. A drill pipe lowering rate may be changed based on the determined surface rate of penetration, and the process may repeat in an iterative cycle until the integral term is reduced to an acceptable degree.

A proportional integral derivative (PID) controller implements control over a drilling system based on an integral term and a proportional term. The integral term is the integral of an operating drilling fluid pressure compared to a target drilling fluid pressure. The proportional term is the difference between an operating weight on bit and a target weight on bit. The sum of the proportional term and the integral term is multiplied by a controller parameter to determine a surface rate of penetration. A drill pipe lowering rate may be changed based on the determined surface rate of penetration, and the process may repeat in an iterative cycle until the integral term is reduced to an acceptable degree.

A method for drilling a subterranean wellbore includes rotating a drill string in the subterranean wellbore to drill the wellbore. The drill string includes a rotary steerable tool or a steerable drill bit including at least first and second axially spaced pads configured to extend radially outward from a tool body and engage a wall of the wellbore. Radial displacements of each of the first and second axially spaced pads are measured while drilling. The measured radial displacements are processed to compute a rate of penetration of drilling.

A drilling control system may access a drilling plan for a borehole comprising one or more of planned path for the borehole, drill string information, mud properties, drill bit properties, formation properties, and drill rig properties. The system may receive a plurality of operating parameters from a rig for the borehole including one or more of an observed toolface, a spindle setting, a rate of penetration, a differential pressure, and a weight-on-bit. The system may receive one or more propagation functions for the borehole determined by a model of the drill string. The system may determine one or more spindle changes or block speed changes based at least in part on the propagation functions and the plurality of operating parameters. The system may generate one or more predicted drill properties from a simulator using the one or more spindle changes or the one or more block speed changes.

A drilling control system may access a drilling plan for a borehole comprising one or more of planned path for the borehole, drill string information, mud properties, drill bit properties, formation properties, and drill rig properties. The system may receive a plurality of operating parameters from a rig for the borehole including one or more of an observed toolface, a spindle setting, a rate of penetration, a differential pressure, and a weight-on-bit. The system may receive one or more propagation functions for the borehole determined by a model of the drill string. The system may determine one or more spindle changes or block speed changes based at least in part on the propagation functions and the plurality of operating parameters. The system may generate one or more predicted drill properties from a simulator using the one or more spindle changes or the one or more block speed changes.

Systems and methods include a computer-implemented method for optimizing well drilling operations. An estimate for a maximum safe rate of penetration (ROP) is determined based on cutting concentrations in annulus (CCA) values. Hydraulics of mud pump+bit and jet impact force hydraulics are evaluated. A developed hole cleaning index is determined based on a carrying capacity model considering chemical and physical influences of drilling fluid rheology. A real-time Drilling Specific Energy (DSE) is determined using the estimate for the maximum safe ROP, the evaluated hydraulics, and the developed hole cleaning index. Optimal drilling parameters are determined using particle swarm optimization (PSO) and a penalty approach (PA). Optimal mechanical drilling parameters are determined using the optimal drilling parameters and by evaluating the real-time DSE. The optimal mechanical drilling parameters are used during drilling. The real-time developed DSE is correlated with fuel consumption to assess CO.sub.2 and toxics gases emission.

Systems and methods include a computer-implemented method for optimizing well drilling operations. An estimate for a maximum safe rate of penetration (ROP) is determined based on cutting concentrations in annulus (CCA) values. Hydraulics of mud pump+bit and jet impact force hydraulics are evaluated. A developed hole cleaning index is determined based on a carrying capacity model considering chemical and physical influences of drilling fluid rheology. A real-time Drilling Specific Energy (DSE) is determined using the estimate for the maximum safe ROP, the evaluated hydraulics, and the developed hole cleaning index. Optimal drilling parameters are determined using particle swarm optimization (PSO) and a penalty approach (PA). Optimal mechanical drilling parameters are determined using the optimal drilling parameters and by evaluating the real-time DSE. The optimal mechanical drilling parameters are used during drilling. The real-time developed DSE is correlated with fuel consumption to assess CO.sub.2 and toxics gases emission.

Drilling operations may be monitored to detect and quantify potential drilling dysfunctions. Using a Bayesian network, potential improvements to drilling operation may be made depending upon the type of dysfunction detected. Suggestions for improved drilling performance may comprise increasing, decreasing, or maintaining one or both of RPM and weight on bit. Suggestions may be presented to an operator as a cone having an apex at the current RPM and weight on bit drilling parameters, with suggestions for modifications to one or both of the RPM and weight on bit corresponding to a cone extending from that apex.

Drilling operations may be monitored to detect and quantify potential drilling dysfunctions. Using a Bayesian network, potential improvements to drilling operation may be made depending upon the type of dysfunction detected. Suggestions for improved drilling performance may comprise increasing, decreasing, or maintaining one or both of RPM and weight on bit. Suggestions may be presented to an operator as a cone having an apex at the current RPM and weight on bit drilling parameters, with suggestions for modifications to one or both of the RPM and weight on bit corresponding to a cone extending from that apex.

A system is described for calculating and outputting micro invisible lost time (MILT). The system may include a processor and a non-transitory computer-readable medium comprising instructions that are executable by the processor to cause the processor to perform various operations. Time-stamp data that includes values of drilling parameters may be received about a drilling operation, and the values of drilling parameters may be classified into a rig state that includes rig activities. For each rig activity, an actual completion time may be determined and compared to an expected completion time for determining a deviation. At least one deviated activity, in which the deviation is greater than a threshold, may be determined. Deviations may be combined into MILT that can be output for controlling the drilling operation.